class_docstr: Leaky version of a Rectified Linear Unit activation layer.
  
  This layer allows a small gradient when the unit is not active.
  
  Formula:
  
  ``` python
  f(x) = alpha * x if x < 0
  f(x) = x if x >= 0
  ```
  
  Example:
  
  ``` python
  leaky_relu_layer = LeakyReLU(negative_slope=0.5)
  input = np.array([-10, -5, 0.0, 5, 10])
  result = leaky_relu_layer(input)
  # result = [-5. , -2.5,  0. ,  5. , 10.]
  ```
  
  Args:
      negative_slope: Float >= 0.0. Negative slope coefficient.
        Defaults to `0.3`.
      **kwargs: Base layer keyword arguments, such as
          `name` and `dtype`.
code: def call(self, inputs):
      return activations.leaky_relu(
          inputs, negative_slope=self.negative_slope
      )
  
file_path: keras/keras/layers/activations/leaky_relu.py
imports: import warnings
  from keras import activations
  from keras.api_export import keras_export
  from keras.layers.layer import Layer
label_desc: Use image node_id 2 for calling the LeakyReLU obj's underlying member method code with example usage: obj.call(inputs) and returns: activations